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[Open Position] Research Fellow on CrowdSourcing and Linked Data - Southampton UK

From: Luis-Daniel Ibáñez <L.D.Ibanez@soton.ac.uk>
Date: Mon, 20 Mar 2017 19:18:35 -0300
To: semantic-web@w3.org
Message-ID: <6cccc2c5-1406-3942-4974-07475bb653a2@soton.ac.uk>
Closing Date:  Wednesday 29 March 2017
Reference:  842617FP

About the role

Candidates should have demonstrable experience (via publications in A 
and A* conferences and journals, participation in research projects, 
organisation of workshops, and similar) in Web and data science, with a 
particular focus on crowdsourcing. The position is for one year.

The candidate should have a PhD* in Computer Science or a related field 
and possess outstanding skills and experience in the area of 
crowdsourcing. Knowledge of Linked Data and Semantic Web technologies is 
a plus.  As a fundamental requirement, candidates must be able to 
communicate and write in fluent English and be willing to contribute to 
collaborative projects. This includes both joint work with other 
institutions and meetings with the project team (quarterly or similar) 
in locations across Europe.

About the QROWD project.

The increased data availability on transportation, traffic, roads, and 
mobility,  from real-time traffic sensors and CCTV streams to social 
media posts and crowdsourced maps, could greatly improve road safety, 
help reduce CO2 emissions, shorten commutes and deliveries, and 
ultimately enhance the quality of life in any European city. QROWD is an 
EU-funded pioneering initiative aiming at creating a socio-technical 
platform for local authorities, service providers and citizens to 
collaboratively take advantage of this wealth of Big Data sources. The 
platform will collect, curate and analyse multiple Big Data sets, 
harmonizing the heterogeneity of data formats employing Linked Data 
tools and standards. It will offer a range of core capabilities that 
support decision making and enable the participatory design of novel and 
location-based apps and transportation policies

QROWD's main outcomes are
   - Open-source software tools to support the five phases of the 
Big-Data Value Chain, combining machine-driven methods performance with 
the knowledge and skill of the crowd intelligence. Particular attention 
is paid to Linked Data fusion and interlinking.
   - Develop a platform to provide an interface for QROWD's algorithms 
and tools as a set of standalone configurable components. Researchers 
and developers will be able to configure their crowdsourcing services, 
monitor them, and seamlessly use their results to make algorithms smarter.
  - Showcase our technology through the delivery of two pilots - one 
with a focus on policy and decision makers in local government  in 
partnership with the city of Trento in Italy; and a second one targeted 
at service providers in the transport space, in partnership with TomTom, 
a global leader in navigation.

Proposed research topics related to the position are:
    - Improve machine learning algorithms for Linked data fusion and 
interlinking with crowdsourcing techniques
    - Develop novel methods of participatory sensing in the context of 
smart transport services based on Linked Data
    - Develop a Crowdsourcing task generator interface: Given a high 
level description of a task, guide the user to choose the most 
appropriate platform and combination of parameters for it.


Detailed information about how to apply can be found in the following 
link: https://jobs.soton.ac.uk/Vacancy.aspx?id=15390&forced=1

Kind Regards,

-- 
Dr. Luis-Daniel Ibáñez
Research Fellow
Web and Internet Science Group
University of Southampton
Received on Tuesday, 21 March 2017 08:03:50 UTC

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